Evaluating potential static liquefaction of tailings to prevent failures. This project aims to reduce risk in the mining industry from failing mine tailings by producing a methodology for predicting the susceptibility of these tailings to static liquefaction. The impact of a mine tailing failure is catastrophic to the downstream community. The project brings together a number of industry partners committed to assisting with verification and adoption of characterisation and designed tools develop ....Evaluating potential static liquefaction of tailings to prevent failures. This project aims to reduce risk in the mining industry from failing mine tailings by producing a methodology for predicting the susceptibility of these tailings to static liquefaction. The impact of a mine tailing failure is catastrophic to the downstream community. The project brings together a number of industry partners committed to assisting with verification and adoption of characterisation and designed tools development in this project. This proposal will integrate results from laboratory element, centrifuge and calibration chamber tests with numerical modelling and in-situ tests to produce a methodology for predicting the susceptibility to static liquefaction.Read moreRead less
Multi-scale modeling of transport through deformable porous materials. Understanding solute transport through porous materials is essential because it provides a technical basis for answering many important questions in society today-how can humans avoid 'brittle bones', how to design durable infrastructure, how to safely store wastes (e.g. hazardous and municipal). Solution of each of these problems requires innovation in model development, new method of analysis, and insightful interpretation ....Multi-scale modeling of transport through deformable porous materials. Understanding solute transport through porous materials is essential because it provides a technical basis for answering many important questions in society today-how can humans avoid 'brittle bones', how to design durable infrastructure, how to safely store wastes (e.g. hazardous and municipal). Solution of each of these problems requires innovation in model development, new method of analysis, and insightful interpretation of results. While theoretical developments of this project are general, in the sense that they are not restricted to particular engineering disciplines, the four chosen applications closely align with two major research priorities namely An Environmental Sustainable Australia and Promoting and Maintaining Good Health.Read moreRead less
Accelerating Consolidation and Closure of Mine Tailings Storage Facilities. All mining operations involve the production of waste. Many regard such waste (tailings) and their environmentally acceptable storage as constituting the largest waste problem on Earth because of the enormous damage and loss-of-life that have resulted from failures of tailings storage facilities. This project focuses on a dewatering technology, electro-osmosis (EO), which has yet to be fully operationalised, for improvin ....Accelerating Consolidation and Closure of Mine Tailings Storage Facilities. All mining operations involve the production of waste. Many regard such waste (tailings) and their environmentally acceptable storage as constituting the largest waste problem on Earth because of the enormous damage and loss-of-life that have resulted from failures of tailings storage facilities. This project focuses on a dewatering technology, electro-osmosis (EO), which has yet to be fully operationalised, for improving the strength, stability and settlement characteristics of the tailings. Sophisticated testing will be undertaken at three scales (lab, meso and, most importantly, field), as well as the development of generic numerical models, to create practical guidelines to facilitate the implementation of EO in mines around the world.Read moreRead less
Hydrogen carbon waste into concrete: AI assisted nanoscience approach. The carbon waste from hydrogen production will be converted into carbon nanosheets on abundant construction materials for the creation of stronger and more durable concrete. Cutting-edge nanoscience-based experiments, as well as sophisticated modelling techniques including machine learning and finite element modelling, will be employed. The findings will drive advances in clean hydrogen production, carbon waste utilisation, c ....Hydrogen carbon waste into concrete: AI assisted nanoscience approach. The carbon waste from hydrogen production will be converted into carbon nanosheets on abundant construction materials for the creation of stronger and more durable concrete. Cutting-edge nanoscience-based experiments, as well as sophisticated modelling techniques including machine learning and finite element modelling, will be employed. The findings will drive advances in clean hydrogen production, carbon waste utilisation, cement hydration, nanotechnology and concrete technology for the next generation of an upskilled workforce and the promotion of a circular economy. This project will be carried out in collaboration with Australian and international renowned experts in computational modelling, nanomaterials and concrete materials.Read moreRead less
Bridge performance assessment through advanced sensing and modelling. Bridge performance assessment through advanced sensing and modelling. This project aims to create cyber infrastructure to manage and maintain civil infrastructure, specifically bridges. Current sensor data interpretation approaches are not good at assessing the performance of civil infrastructure or evaluating the reserve capacity; in particular, they do not adequately account for high levels of systematic modelling uncertaint ....Bridge performance assessment through advanced sensing and modelling. Bridge performance assessment through advanced sensing and modelling. This project aims to create cyber infrastructure to manage and maintain civil infrastructure, specifically bridges. Current sensor data interpretation approaches are not good at assessing the performance of civil infrastructure or evaluating the reserve capacity; in particular, they do not adequately account for high levels of systematic modelling uncertainties. This project intends to ease the current scientific data interpretation bottleneck. Expected outcomes are better infrastructure management and maintenance planning, fewer redundant interventions, modified infrastructure and improved future design.Read moreRead less
Modelling and testing corroding reinforced concrete structures. The project aims to develop models and methods to enable the early detection of active steel corrosion. Most of Australia’s critical infrastructure is located on or near the coast in high saline conditions and is exposed to a high risk of reinforcing steel corrosion. Our ability to design and monitor such structures is crucial. The first part of the project aims to develop an innovative finite element model to improve the prediction ....Modelling and testing corroding reinforced concrete structures. The project aims to develop models and methods to enable the early detection of active steel corrosion. Most of Australia’s critical infrastructure is located on or near the coast in high saline conditions and is exposed to a high risk of reinforcing steel corrosion. Our ability to design and monitor such structures is crucial. The first part of the project aims to develop an innovative finite element model to improve the prediction of both active steel reinforcement corrosion and the time to concrete cracking in a chloride environment. It then plans to develop a non-destructive method, combining ultrasonic waves-based technology and acoustic emission, to detect active steel corrosion before any damage is visible on the structure.Read moreRead less
AI Assisted Probabilistic Structural Health Monitoring with Uncertain Data. This project aims to develop an advanced Artificial Intelligence (AI) assisted probabilistic structural health monitoring approach for civil engineering structures. The developed approach applies novel deep learning techniques with a large amount of data measured from uncertain and complex environment, for reliable structural condition monitoring and performance prediction. This project expects to make a step change in d ....AI Assisted Probabilistic Structural Health Monitoring with Uncertain Data. This project aims to develop an advanced Artificial Intelligence (AI) assisted probabilistic structural health monitoring approach for civil engineering structures. The developed approach applies novel deep learning techniques with a large amount of data measured from uncertain and complex environment, for reliable structural condition monitoring and performance prediction. This project expects to make a step change in data mining and interpretation. Expected outcomes of the project include novel AI assisted approaches to conduct probabilistic structural condition monitoring with sensitive features and future structural performance prediction. This will provide significant benefits to infrastructure asset owners to reduce maintenance costs.Read moreRead less
Advancing laterally loaded pile analysis. This project will replace out-of-date solution techniques for the design of pile foundations subjected to wind, waves and other horizontally applied forces and, in so doing, lead to more efficient designs of the foundations for structures such as elevated highways, tall buildings, bridges, jetties, towers, wind turbines and offshore platforms.
Mitigating the risk of cyanobacterial blooms in wastewater ponds. Cyanobacterial blooms in wastewater treatment plants impact on effluent quality and the utility of recycled water, posing a significant risk to the economy, the environment and public health. To understand the causes of cyanobacterial blooms in pond-based wastewater treatment plants and the risk they pose, this project will use the latest molecular techniques to examine how the microbial communities within these systems interact w ....Mitigating the risk of cyanobacterial blooms in wastewater ponds. Cyanobacterial blooms in wastewater treatment plants impact on effluent quality and the utility of recycled water, posing a significant risk to the economy, the environment and public health. To understand the causes of cyanobacterial blooms in pond-based wastewater treatment plants and the risk they pose, this project will use the latest molecular techniques to examine how the microbial communities within these systems interact with each other and their surrounding environment to form blooms and produce toxins and other harmful metabolites. Such knowledge will inform risk assessment and provide strategies for the mitigation of future bloom events, improving the security of our increasingly valuable recycled water resources.Read moreRead less
Prediction and controlling of pipe failures in buried water and gas pipe systems. Australian Research Council has recognised water as a critical resource that must be protected from wastage. Along with water, the supply of gas to communities through extensive buried pipe networks is an essential service. As the pipe systems age, the pipe failures have increased. These failures lead to loss of valuable commodity and inconvenience and health hazard to public and workers. Effective asset manage ....Prediction and controlling of pipe failures in buried water and gas pipe systems. Australian Research Council has recognised water as a critical resource that must be protected from wastage. Along with water, the supply of gas to communities through extensive buried pipe networks is an essential service. As the pipe systems age, the pipe failures have increased. These failures lead to loss of valuable commodity and inconvenience and health hazard to public and workers. Effective asset management tools are urgently required in predicting and controlling pipe failures. A consortium of water and gas suppliers and a team of researchers from Monash University and CSIRO have joined forces to address this problem so that significant social and economic benefits to Australia can be realised. Read moreRead less